Dynamic connectivity patterns predict cognitive decline after neurosurgery

In a collaboration between the CCA VUmc Brain Tumor Center, Amsterdam Neuroscience, and the VUmc MEG center, we investigated the association between dynamics of “functional connectivity” and cognitive outcome in patients undergoing neurosurgery. The study, which was published in Scientific Reports, shows that preoperative measurement of these dynamics may be essential for predicting whether patients will or will not develop problems with their cognitive functioning after undergoing neurosurgery.

Resective neurosurgery, which is a commonly used treatment for brain tumors and other lesions causing epileptic seizures, sometimes leads to postoperative cognitive deterioration. Unfortunately, it has been difficult to predict which patients are at risk for developing these impactful cognitive problems. Therefore, we used an innovative approach to determine the characteristics of communication patterns throughout the brain before and after such surgery. We hypothesized that a pathologically increased level of communication, particularly of the regions in the brain that are already considered ‘hubs’, would be indicative of future cognitive problems. A rail network offers a nice analogy of this ‘hub overload’ hypothesis. If a train or rail becomes defect at some time, other trains may be rerouted. This causes an increase of trains passing through the surrounding train stations. The increase in traffic flow may cause delays in the regularly scheduled trains passing through these stations, which may then spread through an even bigger number of train stations. Now imagine that the first defect train was situated near a hub train station: this would probably cause an even bigger, and faster, cascade of delays throughout the entire rail network. Likewise, large amounts of traffic flow through a healthy brain network, particularly via the hub regions. In the case of a local problem, such as a brain tumor or other lesion, the rerouting of flow may be related to hub overload and be predictive of subsequent deterioration of the brain network.

Twenty-eight patients with lesions causing epilepsy (mostly primary brain tumors) underwent magnetoencephalography, which is a unique technique used to measure brain activity in real-time. Patients 
also underwent neuropsychological assessments preoperatively and 1-year after neurosurgery to test their cognitive functioning. Patients’ hub load was determined by investigating communication and dynamics of hub regions with the rest of the brain. Results show that deteriorating memory functioning was indeed correlated with higher hub load. Moreover, it was even possible to predict which patients would develop cognitive problems using only the preoperative hub load measurement. Although the study needs to be replicated, these findings suggesting that this measure of hub load may be used as a prognostic marker for tailored treatment planning in surgical candidates.

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